AMD Looks to Infinity for AI Interconnects
![Image](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjbSeUW94GJVWLwYhTBj2EXLWIY6IiaHhfmbLk2b8cQw2ANtzXMFIPhPa6ezapF78GuEHLd2y-lWjdPcLTWZg8JR3155NoSfGEbWXBgV5zgLN0WuKt2LT-IY6QdQX4CY_MiL7TccXDp39H0VJSzqo8qg6pSexZTDiWsugv1iAMAI56cqY18gg8S1m8NtDs/s320/AI%20NIC%20with%20XGMI.png)
With the formal launch of the MI300 GPU, AMD revealed new plans for scaling the multi-GPU interconnects vital to AI-training performance. The company's approach relies on a partner ecosystem, which stands in stark contrast with NVIDIA's end-to-end solutions. The plans revolve around AMD's proprietary Infinity Fabric and its underlying XGMI interconnect. Infinity Fabric Adopts Switching As with its prior generation, AMD uses XGMI to connect multiple MI300 GPUs in what it calls a hive. The hive shares a homogeneous memory space formed by the HBM attached to each GPU. In current designs, the GPUs connect directly using XGMI in a mesh or ring topology. Each MI300X GPU has up to seven Infinity Fabric links, each with 16 lanes. The 4th-gen Infinity Fabric supports up to 32Gbps per lane, yielding 128GB/s of bidirectional bandwidth per link. At the MI300 launch, Broadcom announced that its next-generation PCI Express (PCIe) switch chip will add support for XGMI. At last October'